Product recall - how do you instantly scale when it is needed and what are the challenges

Tom and Steve discuss the challenges around scaling up to deal with product recalls and automating the inbound and outbound calls or multichannel responses?

With time sensitive recalls that can be public health issues, we talk about how automating this can be scaled instantly from a passive service and triggered when needed.

Our latest series of podcasts, concentrates on voice and how that is going to impact the next few years with tips along the way. Find out more about voicebots here and if you have any subjects that you would like us to discuss then email info@disruptionworks.co.uk with the subject Podcast and we will see what we can do ;-)

Transcript

0:0:5.900 --> 0:0:15.160
 Steve Tomkinson
 Hello everybody and welcome to another edition of disruption works chit chat with Tom and Steve. How you doing, Tom? How are you today?

0:0:14.800 --> 0:0:16.850
 tom
 I'm fine, Steve. Thank you. How are you?

0:0:16.900 --> 0:0:25.420
 Steve Tomkinson
 Yeah, not so bad. Not so bad. I'm starting to build me distance up. You do a bit of running on the old on the side, don't you? Do you just still still run time?

0:0:26.200 --> 0:0:31.600
 tom
 Like actually picked it up for not so long ago. Seriously again. And it had all to do with.

0:0:38.250 --> 0:0:38.920
 Steve Tomkinson
 Ohh yeah.

0:1:0.30 --> 0:1:1.20
 Steve Tomkinson
 Ohh okay.

0:0:32.420 --> 0:1:1.280
 tom
 And sort of break I had with in my personal life with the taking your little little pause with would running, but also of course with with the stupid winters here. So I actually for your information and I today at my times are you your time but said the European time I was running from from 12:15 until 2:00 o'clock in the dunes here with my dog. So that's what like yeah.

0:1:1.770 --> 0:1:2.490
 Steve Tomkinson
 Really. Wow.

0:1:6.800 --> 0:1:7.530
 Steve Tomkinson
 Ohh cool.

0:1:9.670 --> 0:1:10.560
 Steve Tomkinson
 Yeah, yeah.

0:1:2.130 --> 0:1:12.230
 tom
 So no, so about 1313 kilometres and and that's and that's easy. Yeah, and not too fast. That's going nicely.

0:1:11.330 --> 0:1:13.680
 Steve Tomkinson
 No, just just jogging along, isn't it?

0:1:13.410 --> 0:1:14.650
 tom
 Exactly. Yeah, yeah.

0:1:14.940 --> 0:1:15.460
 Steve Tomkinson
 Yeah, well.

0:1:19.790 --> 0:1:22.540
 tom
 Yeah, you had problem. Your answering. Yeah, yeah.

0:1:25.470 --> 0:1:25.960
 tom
 It was good.

0:1:28.210 --> 0:1:28.640
 tom
 Yeah.

0:1:30.720 --> 0:1:31.300
 tom
 It's good.

0:1:35.780 --> 0:1:36.230
 tom
 Okay.

0:1:16.700 --> 0:1:37.70
 Steve Tomkinson
 I'm trying to build mine up cause I did not hamstring. So yeah just chilling. So I've done. Yeah, yeah. But it's it's good now. I've got this sign off. So I'm 12K. This weekend is mid plan to keep the keep the distance going up so 12141618 and I've got 1/2 marathon coming up so we'll see.

0:1:37.210 --> 0:1:39.250
 tom
 Ohh, that's good, that's good. That's good.

0:2:0.210 --> 0:2:0.950
 Steve Tomkinson
 The iOS say.

0:2:1.740 --> 0:2:2.20
 Steve Tomkinson
 Yeah.

0:1:39.920 --> 0:2:2.310
 tom
 No, but I mean I'm. I I have. I have started to run again. So I I'm now trying to not every other day but one day running two days balls one day running two day polls to begin with and then I'll I'll win in within two weeks I will probably change that to each and every other of every other day running the distance and then.

0:2:3.220 --> 0:2:9.130
 tom
 And once with the dog and once without the dog because the dog wants to sniff all places and then.

0:2:10.340 --> 0:2:11.400
 Steve Tomkinson
 That's the problem with it.

0:2:14.780 --> 0:2:15.200
 Steve Tomkinson
 Yeah.

0:2:25.270 --> 0:2:26.130
 Steve Tomkinson
 That's right.

0:2:11.210 --> 0:2:27.820
 tom
 And then you'll standstill again. You run a little bit and you still again and it's much that's also OK. It's also good training by the way, but it's also of course interesting to not have to take account for the dog that needs to stifle all the flowers and all the stuff that's around.

0:2:27.290 --> 0:2:29.270
 Steve Tomkinson
 Get get dragged into the junes.

0:2:32.910 --> 0:2:33.340
 Steve Tomkinson
 Get a.

0:2:29.740 --> 0:2:39.960
 tom
 Exactly. Exactly. No. She's she's very she's very curious. And so we run like for 25 metres and then stop again and then we run stop again.

0:2:43.370 --> 0:2:43.720
 tom
 Yeah.

0:2:52.190 --> 0:2:52.620
 tom
 Hmm.

0:2:42.420 --> 0:2:55.90
 Steve Tomkinson
 Yeah, so ohh well to the podcast. I suppose we've talked about a few years cases and things, but I yeah, I wanted to cover something. That's.

0:2:56.340 --> 0:2:59.750
 Steve Tomkinson
 No, everybody's horizon, but product recalls.

0:3:0.510 --> 0:3:8.310
 Steve Tomkinson
 Uh, which is a, which is a big process in the background of most consumer businesses.

0:3:8.950 --> 0:3:39.320
 Steve Tomkinson
 Um, be looking around at use cases for product recall, and there's a lot of automation in the process or people are trying to, but there's also a serious amount of phone calling. Emailing following up on emails, phone up on a recall where we haven't had it all, that type of stuff. So lots of process that needs to be scaled kind of very quickly because these are never planned for things cause it's a it's an incident. But also then you have to have some.

0:3:39.600 --> 0:3:40.20
 Steve Tomkinson
 Kind of.

0:3:41.180 --> 0:3:47.30
 Steve Tomkinson
 Process. That's that you can scale on demand, which is as we all know, it's really tricky at the moment.

0:3:48.760 --> 0:3:59.90
 Steve Tomkinson
 So I was looking at one case study of some guys in in the States and Dev 750 product recalls a year.

0:4:0.500 --> 0:4:1.100
 Steve Tomkinson
 That's like.

0:4:0.720 --> 0:4:1.910
 tom
 750.

0:4:2.220 --> 0:4:14.840
 Steve Tomkinson
 Yeah. Yeah. So they have 750 items. They have to recall from their consumers. We Can you imagine how much work that is? That is just horrendous. I mean they are food related. So it's quite.

0:4:22.160 --> 0:4:22.970
 tom
 Yeah, of course.

0:4:16.280 --> 0:4:24.840
 Steve Tomkinson
 It's quite urgent as well, you know. So food's gonna always be a problem because it's, you know, there's there's there's a health, health and safety issue.

0:4:25.480 --> 0:4:25.770
 tom
 Yeah.

0:4:25.690 --> 0:4:29.550
 Steve Tomkinson
 Um, but but the principles that used that.

0:4:30.880 --> 0:4:55.670
 Steve Tomkinson
 That are currently the case is that you have a contact centre that's kind of ready to go, so you have this ongoing contract where you might or might not need it and you know you're scale it when you need it. And of course you know you have 50,000 products out there that you need to get recalled. That's a lot of people you need to go through that data and contact those people. You know, it's crazy mad.

0:5:13.850 --> 0:5:14.290
 tom
 Yeah.

0:4:56.850 --> 0:5:16.140
 Steve Tomkinson
 So the obvious thing is to have something that can scale on demand and and doing the multi channel thing that we talked about last time and having a voice, but that just does the work for you and really, truly automates that conversation just seems like the right choice you know.

0:5:16.580 --> 0:5:17.250
 tom
 Exactly.

0:5:18.260 --> 0:5:32.700
 Steve Tomkinson
 I mean, we've done her quite a lot in identification and stuff like that and making sure we're talking to the right people and that's not really a problem, but product or identifications are tricky. 1, isn't it, you know.

0:5:32.720 --> 0:5:34.830
 tom
 Yeah, I mean.

0:5:42.900 --> 0:5:43.240
 Steve Tomkinson
 Yeah.

0:5:36.150 --> 0:5:46.50
 tom
 Imagine that you are dealing with a broad variety of products. Could be anything, even think about clothing. For instance you have you have such a variety of products in.

0:5:52.700 --> 0:5:53.0
 Steve Tomkinson
 Yeah.

0:6:9.530 --> 0:6:10.140
 Steve Tomkinson
 Yeah.

0:5:46.960 --> 0:6:16.860
 tom
 There are so many items and how to how to separate one item from the other one by speech is of course difficult, especially when people start to sort of describe the problem. You knew the blue jeans with you know blah blah. It gets very hard for the for the voice bought. You understand exactly what kind of items is all about. But then again we know that items that you buy over the Internet have a product code or they have.

0:6:21.780 --> 0:6:22.220
 Steve Tomkinson
 Yeah.

0:6:17.320 --> 0:6:31.250
 tom
 No article code or a registration code. Something is always there, which is very very easy to use and for your information and for our listeners, this is something which is really fantastic actually because.

0:6:40.310 --> 0:6:40.580
 Steve Tomkinson
 Right.

0:6:32.850 --> 0:6:42.400
 tom
 Quite some time ago we had an issue with number recognition when it when it comes to speech recognition, number recognition was always the delicate you know.

0:6:43.160 --> 0:6:57.490
 tom
 2345 and sometimes the machine mixed it up, and of course then you have a problem. But today, because we use the incredible competence of the API machines in the cloud.

0:6:58.710 --> 0:7:3.650
 tom
 The even the elf in the miracle number recognition is.

0:7:6.690 --> 0:7:7.90
 Steve Tomkinson
 Yeah.

0:7:13.520 --> 0:7:13.790
 Steve Tomkinson
 Yeah.

0:7:23.870 --> 0:7:24.170
 Steve Tomkinson
 Yeah.

0:7:25.480 --> 0:7:25.810
 Steve Tomkinson
 Yeah.

0:7:4.800 --> 0:7:31.300
 tom
 Almost 100% solid so and and you can even do a double cheque. I mean if you would ask for it alphanumerical number and you would you would say something like okay. This is about the Levi's blue jeans, right? And if you get a no, then you can always have a sort of intelligent follback error handling that that, that that picks up the situation without losing the caller. But yeah. So.

0:7:37.710 --> 0:7:38.40
 Steve Tomkinson
 Yeah.

0:7:32.190 --> 0:7:43.790
 tom
 Yes, we could do a great job with speech recognition here as well because this not alphanumerical number understanding is so incredibly accurate today.

0:7:55.190 --> 0:7:57.120
 tom
 And there's already given you. Yeah, yeah.

0:7:44.400 --> 0:7:58.250
 Steve Tomkinson
 Yeah, yeah, yeah, I suppose we can still do the matches on on a product item. And of course, if we're going outbound, then we know what the product is. So the description, the product is something that's transcripted out. Yeah, it's, it's, it's easy enough.

0:7:58.380 --> 0:7:58.740
 tom
 Yeah.

0:7:59.260 --> 0:8:2.470
 Steve Tomkinson
 It's it's the inbound called, but I suppose if the inbound.

0:8:9.480 --> 0:8:10.900
 tom
 Yes, yes.

0:8:2.810 --> 0:8:15.920
 Steve Tomkinson
 And when we're managing that, then again, they're reasonably informed because they are phoning about something, so they know what it's about as well, you know, um. And and if we're dealing with categories of. Yeah.

0:8:19.530 --> 0:8:19.820
 Steve Tomkinson
 Yeah.

0:8:13.300 --> 0:8:21.850
 tom
 And people have the data as well. You know they will have the data as well because when you get the package sent to your home, there's always some kind of data included, right?

0:8:26.450 --> 0:8:26.800
 tom
 Yes.

0:8:22.230 --> 0:8:28.150
 Steve Tomkinson
 Yeah. Yeah, that's right. And then now it's all data received as far as emails concerned and all that type of stuff anyway.

0:8:28.740 --> 0:8:33.910
 tom
 And I don't know, Steve, if I may say so, but I'm I mean if you order something from the Internet.

0:8:39.620 --> 0:8:40.60
 Steve Tomkinson
 Yeah.

0:8:52.180 --> 0:8:52.540
 Steve Tomkinson
 Yeah.

0:8:34.650 --> 0:8:53.340
 tom
 Um online. There's always some kind of dating you need to provide, and either your e-mail address or your phone number or something like that. And then it's also very elegant to use in these processes because we when we have a phone number and we have a an earlier data set, then we can of course.

0:8:54.480 --> 0:8:55.210
 tom
 Refer to you.

0:8:55.950 --> 0:9:7.880
 Steve Tomkinson
 Yeah, and and and of course communicate vitamin as well. So if we need any sort of verification or anything like that, then you can do the multi channel, send them an e-mail. So just follow the link. I'm just about to send you an e-mail.

0:9:6.800 --> 0:9:9.470
 tom
 Exactly. Exactly. Yeah.

0:9:9.270 --> 0:9:12.280
 Steve Tomkinson
 Something so all that kind of what does quite well.

0:9:12.420 --> 0:9:16.870
 Steve Tomkinson
 And in that regard, and I spoke, and I suppose in addition to that.

0:9:18.330 --> 0:9:19.880
 Steve Tomkinson
 We've actually got quite a nice.

0:9:20.890 --> 0:9:22.930
 Steve Tomkinson
 Scaled option there where.

0:9:23.720 --> 0:9:27.940
 Steve Tomkinson
 Really, you're just feeding the bot data to go and do this job. You know you've got.

0:9:45.440 --> 0:9:45.950
 tom
 Hmm.

0:9:29.180 --> 0:9:50.760
 Steve Tomkinson
 40,000 records of consumers that have bought these products, you know, loyalty data, bits like that are all pretty amazing now. So you know, if you've you've got those little bits of data that are then useful for the customer to then get notified that we saw you bought this and it we want to recall it.

0:9:51.680 --> 0:9:52.610
 Steve Tomkinson
 Then that's.

0:9:56.880 --> 0:9:57.350
 tom
 Exactly.

0:9:57.420 --> 0:10:10.260
 Steve Tomkinson
 Clients perspective, especially in in like the Food Standards area. Then you can demonstrate that you can react really quickly to anything that's a health scare or anything that's much more.

0:10:11.400 --> 0:10:16.180
 Steve Tomkinson
 You know, you know, time sensitive, you know, but you can't do any other way.

0:10:17.150 --> 0:10:26.760
 tom
 Yeah, I totally agree with you. What? What strikes me most is that when we're talking about solutions in this in this particular area, so it's been.

0:10:28.680 --> 0:10:32.570
 tom
 Does it limitations are not on the front and or not on the side of the voice?

0:10:33.120 --> 0:10:33.440
 Steve Tomkinson
 No.

0:10:33.430 --> 0:10:39.90
 tom
 And there's nothing decided the speech recognition limitations often are on the side of the data structure of the customer.

0:10:39.640 --> 0:10:40.90
 Steve Tomkinson
 Yeah.

0:10:46.630 --> 0:10:46.940
 Steve Tomkinson
 Yeah.

0:10:39.990 --> 0:10:59.190
 tom
 So for business customers, so the business customer has a certain infrastructure and they have their processes. And what strikes me each and every time again it's not not that long ago I had a the phone call with a potential customer who is who is setting up a European car lease system.

0:10:59.560 --> 0:11:0.290
 Steve Tomkinson
 Ohh yeah.

0:10:59.890 --> 0:11:0.800
 tom
 And.

0:11:2.430 --> 0:11:15.620
 tom
 So they wanted to do something with voice recognition. And I said, well, that of course that's great because if you wanna rent a car or hire a car or whatever and you need, suddenly you have some problems that you need to report some problems.

0:11:18.410 --> 0:11:19.820
 Steve Tomkinson
 Yeah, yeah.

0:11:25.270 --> 0:11:25.760
 Steve Tomkinson
 Yeah.

0:11:16.370 --> 0:11:32.340
 tom
 It's suited for speech recognition perfectly. So then I said well then of course we need to have access to your client database and he told me, well, we haven't got, we haven't come to a right structure of our client database to begin with.

0:11:33.150 --> 0:11:43.810
 tom
 And I said, well, if you don't have a really good back end structure and and an infrastructure on your on your client database, of course we cannot start with speech recognition is imposs.

0:11:44.390 --> 0:11:44.930
 Steve Tomkinson
 Yeah, yeah.

0:11:44.580 --> 0:11:46.70
 tom
 Because she we need the data.

0:11:46.620 --> 0:11:49.330
 Steve Tomkinson
 Well, you can't really do it with a human.

0:11:50.250 --> 0:11:51.250
 Steve Tomkinson
 If you haven't got the data.

0:11:52.510 --> 0:11:53.40
 Steve Tomkinson
 Yes.

0:11:51.560 --> 0:11:57.370
 tom
 Exactly. Okay you can talk. You can talk a lot and maybe you can try to find love, but you will be very expensive goals.

0:12:1.150 --> 0:12:1.470
 tom
 Yeah.

0:12:5.90 --> 0:12:5.740
 tom
 Yeah.

0:11:58.230 --> 0:12:8.450
 Steve Tomkinson
 Yeah, take a while. Take a while. It sounds like that sounds like a an inspector clueso type of arrangement. It's gonna take you some time to sort that out.

0:12:9.570 --> 0:12:12.50
 Steve Tomkinson
 Yeah. Well, I, well, yeah, I'd already mean.

0:12:9.20 --> 0:12:16.310
 tom
 Yeah, if you know, I mean for them in, in their goal centre in their cool centre, it was like average goal was like 32 minutes.

0:12:16.740 --> 0:12:17.540
 Steve Tomkinson
 Wow.

0:12:17.190 --> 0:12:19.820
 tom
 And is it? Well, that's that's really a waste of space and time.

0:12:20.220 --> 0:12:22.940
 Steve Tomkinson
 Yeah, that's a lot. Neh 32 minutes.

0:12:30.420 --> 0:12:30.710
 Steve Tomkinson
 Yeah.

0:12:33.720 --> 0:12:34.330
 Steve Tomkinson
 Yeah, yeah.

0:12:22.380 --> 0:12:37.230
 tom
 Yeah, because very expensive. And I mean if if you if you know that you have to pay like €580 per month to lease this car and it's not even a big car, then I think well, that's also realistic money, isn't it?

0:12:37.620 --> 0:12:40.20
 Steve Tomkinson
 Yeah. Jesus, that's.

0:12:38.780 --> 0:12:47.130
 tom
 And then part of that money goes into goal, said we guys because they have to, you have to, you have to spend 32 minutes on your call. Yeah, that's it. And if you know then that.

0:12:46.100 --> 0:12:50.60
 Steve Tomkinson
 Well, that's because, and that's because they're all in Inspector Clouseau's as well.

0:12:50.820 --> 0:12:51.410
 Steve Tomkinson
 Yeah.

0:12:58.40 --> 0:12:58.250
 Steve Tomkinson
 Yeah.

0:12:50.310 --> 0:13:3.30
 tom
 Yeah, and and do not. Let's not forget that and Everage Western European coal handled by coal centre is about between 5:00 and 5:00, EUR 20 a minute.

0:13:4.990 --> 0:13:5.480
 tom
 Ohh.

0:13:7.110 --> 0:13:8.950
 tom
 That's a lot of money, yeah.

0:13:3.600 --> 0:13:11.70
 Steve Tomkinson
 Wow. Wow, that's a less a lot of money. Just straight out the door that's off the bottom line. That's just that's wasted money, isn't it?

0:13:11.630 --> 0:13:12.940
 tom
 Isn't it? Of course.

0:13:12.410 --> 0:13:14.680
 Steve Tomkinson
 Yeah, crazy. Well, I suppose.

0:13:16.80 --> 0:13:25.190
 Steve Tomkinson
 Yeah, the data has to be right, but I, but I feel that once you've most retailers now are pretty on that and especially the online retailers and but even.

0:13:26.840 --> 0:13:28.410
 Steve Tomkinson
 Even with the.

0:13:29.510 --> 0:13:49.940
 Steve Tomkinson
 High St retailers, they tend to be very well structured as far as their day is concerned and even digitise it, you know. So I'm getting asked now pretty much every time I buy something in a shop. Do you want your you want your receipt e-mail to you you know because they want to start nurturing data on me, you know? And and it's convenient for me as well.

0:13:58.330 --> 0:13:58.890
 Steve Tomkinson
 Yeah.

0:13:50.580 --> 0:14:2.380
 tom
 Yeah. Let me be a little bit provocative. So let me ask you, just between us, let me ask you where does voice recognition bring the added value in this context?

0:14:10.270 --> 0:14:11.50
 tom
 That's for sure.

0:14:22.850 --> 0:14:23.220
 tom
 Well.

0:14:4.940 --> 0:14:33.480
 Steve Tomkinson
 Well, it's uh, time, isn't that? Surely scalability is going to be massive, you know, cause you you've got it, you cause you can't get the people without paying an absolute fortune for the people we just found out how much they're they are. But also it's not just that it's the customer experience you know. Because if you can do if you can you've got a product recall if you've got a hang on the phone to try and sort it out you're going to be properly annoyed at the fact that you've.

0:14:32.230 --> 0:14:38.480
 tom
 Or you're putting in waiting queue because all the people are busy at the moment and you have to wait and wait and wait until you get someone on the phone.

0:14:36.880 --> 0:14:41.760
 Steve Tomkinson
 Ohh. Joking. That's the that's the that's the big benefit.

0:14:39.440 --> 0:14:52.370
 tom
 Yeah, but here you already you already point out three. Three really good reasons why speech recognition would be an added value in that context, and that's something I think we need to point out more because.

0:14:53.470 --> 0:15:2.110
 tom
 You you bring up a very good, very good idiom, and you you talk about product recall. OK, perfectly. OK.

0:15:8.330 --> 0:15:8.730
 Steve Tomkinson
 Yeah.

0:15:13.340 --> 0:15:13.580
 Steve Tomkinson
 Yeah.

0:15:3.580 --> 0:15:18.730
 tom
 We we are, we are. We are working together with speech recognition and we're trying to to to inform our public about the the the advantages and the possibilities and the potential of speech. But again and again, I'm trying to emphasise.

0:15:19.760 --> 0:15:27.50
 tom
 The working with speech recognition truly brings an added value. For instance, what? You just what you just brought up.

0:15:27.830 --> 0:15:28.910
 tom
 Customer satisfaction.

0:15:29.490 --> 0:15:29.800
 Steve Tomkinson
 Yeah.

0:15:29.840 --> 0:15:30.450
 tom
 And.

0:15:31.490 --> 0:15:33.470
 tom
 Working with voice, very easy to do.

0:15:34.70 --> 0:15:39.200
 tom
 And keeping a a high level and high level customer service to begin with.

0:15:39.510 --> 0:15:39.810
 Steve Tomkinson
 Yeah.

0:15:46.850 --> 0:15:47.140
 Steve Tomkinson
 Yeah.

0:15:40.20 --> 0:15:47.190
 tom
 And addressing people in in, in, in, in the channel, they know best speech easy.

0:15:47.870 --> 0:15:48.130
 Steve Tomkinson
 Yeah.

0:15:48.260 --> 0:15:48.450
 tom
 Ohh.

0:15:49.290 --> 0:15:54.900
 Steve Tomkinson
 Ohh no, you're absolutely right. And and I think the well we're using bots just for that. You know just for MPs.

0:15:55.280 --> 0:16:2.870
 Steve Tomkinson
 I'm scores and things like that because the customer experience is massively important. You know, two understand what that.

0:16:3.20 --> 0:16:3.610
 Steve Tomkinson
 And.

0:16:4.760 --> 0:16:11.900
 Steve Tomkinson
 You know what benefit that asked to your business? It's gotta be there. The thing is, what you're doing. What? You. Yeah.

0:16:13.970 --> 0:16:14.500
 Steve Tomkinson
 Ohh yeah.

0:16:9.360 --> 0:16:17.140
 tom
 Perceived perceived as yeah, perceived customer services. Even more important, I mean the if the customer feels that he's really, yeah.

0:16:19.140 --> 0:16:19.740
 tom
 Exactly.

0:16:22.220 --> 0:16:22.890
 tom
 Exactly.

0:16:15.730 --> 0:16:40.150
 Steve Tomkinson
 The product recall is a negative. It's a negative journey, but if you can make it a nice and easy positive journey, but you know most of the product recalls, what happens is that they go right. This is what we're going to do. We're gonna. We've gotta get all this stuff back and we're gonna give that person a 10% off voucher and a refund for their item, you know, or whatever it may be. You know, some sort of voucher say.

0:16:41.620 --> 0:16:56.280
 Steve Tomkinson
 She can do that, but also that it hasn't been difficult for them to do it and they haven't given up in the process. So they've done ended up with those pair of jeans they didn't want and they've just gone well. I tried to resend them back, but it was so complicated and I I gave up.

0:17:2.420 --> 0:17:2.890
 tom
 Hmm.

0:17:23.530 --> 0:17:23.900
 tom
 Hmm.

0:16:57.0 --> 0:17:26.350
 Steve Tomkinson
 And they were going to give me 10% and me money back, but that it was just all too painful. But if you, but if the it's then dealt with properly, you then have the conversation which goes do you know what don't that company. I bought those jeans from they had a bit of a the seams were going on the sides but do you know they took it straight back off me they gave me a £10 voucher and yeah no I bought another pair. Ohh definitely you know cause and do you know the great.

0:17:27.110 --> 0:17:28.470
 Steve Tomkinson
 Totally different.

0:17:26.810 --> 0:17:35.30
 tom
 And they were very friendly and they were very, very, very serious minded. And I was held directly. It didn't have to wait in the waiting queue and I got the service I needed right away.

0:17:36.190 --> 0:17:36.540
 tom
 Ohh.

0:17:35.410 --> 0:17:41.550
 Steve Tomkinson
 Yeah. Do you know what the the the best example I had to that was. So I had Alexis and.

0:17:49.720 --> 0:17:50.100
 tom
 Yeah.

0:17:42.410 --> 0:17:55.600
 Steve Tomkinson
 And Toyota would very obviously Lexus's Toyota luxury branding and um and they were slated for doing lots of recalls. But tell you what they're like 1.

0:17:56.80 --> 0:18:5.580
 Steve Tomkinson
 When I I had to recall on my Lexus. It was just a part I didn't know. They got old to me, they said we've got something we need to do on your car. It's a.

0:18:18.570 --> 0:18:18.890
 tom
 Yeah.

0:18:6.440 --> 0:18:34.190
 Steve Tomkinson
 It was something to do with the transmission. Nothing too extraordinary. But it was something they said. No, we found a fault with it. We want to change it. So can we. Book it in. Booked it in with them all this just to process. Booked it all, then went in, sorted out. They did a valet on the car. It was all lovely and shiny. Gave it back to me. And I thought that's fantastic because it was just dealt with. It was super easy to do it would. They'd done it professionally.

0:18:34.850 --> 0:18:46.60
 Steve Tomkinson
 I didn't know there was problem, it wasn't affecting me. It wasn't affecting my driving, but they knew that it was on its way out. So that whole, the fact that was a fault, something wrong with the car, which is a real negative.

0:18:46.600 --> 0:18:49.240
 tom
 Hmm, well, starting to a positive.

0:18:49.940 --> 0:18:50.670
 tom
 Yeah.

0:18:52.590 --> 0:18:52.930
 tom
 Yep.

0:18:54.650 --> 0:18:55.70
 tom
 Yeah.

0:18:47.740 --> 0:19:0.50
 Steve Tomkinson
 Was sent into a total positive because I went there looking after me because they've changed it before it went wrong. They've it was dead easy to do. They booked me in when it was convenient for me, not for them.

0:19:0.820 --> 0:19:14.480
 Steve Tomkinson
 And just want. There you go. I gave me a full proper courtesy car. Nice version of the car I had. You know. So it was all nice. So it didn't inconvenience me at all. In fact, do you know what they did?

0:19:15.160 --> 0:19:20.260
 Steve Tomkinson
 They came and collected the car and took it away, gave me another one, brought the car back, took the other car away.

0:19:21.40 --> 0:19:22.140
 tom
 No, that perfect.

0:19:21.820 --> 0:19:25.940
 Steve Tomkinson
 So it didn't make any difference to me at all. I was still driving around in Alexis.

0:19:25.600 --> 0:19:34.50
 tom
 No. What did the very the very, very composition you just used a negative situation turned into something very positive.

0:19:34.940 --> 0:19:36.560
 tom
 And that's the whole thing.

0:19:39.950 --> 0:19:40.320
 tom
 Yeah.

0:19:34.540 --> 0:19:52.910
 Steve Tomkinson
 Yeah, which which recalls can be so bad. You know there can be so so bad. And if you've got any sort of scare and there's any sort of like with a dimensioned earlier, just like health scare stuff cause it's food related running that stuff you need to be on that you need to be there and need to be going. We have this, this is what it is.

0:19:53.290 --> 0:20:5.340
 Steve Tomkinson
 Did that, but we want to just get it sorted out. Yeah, I'll send a return slip in a in your e-mail. Send it to us, or please destroy it and throw away. But you know.

0:20:14.880 --> 0:20:15.250
 tom
 No.

0:20:17.690 --> 0:20:18.30
 tom
 No.

0:20:6.430 --> 0:20:30.510
 Steve Tomkinson
 They sent us a picture back on the e-mail just to confirm it's the right product and now we'll get a voucher over to you for £10. Whatever it is, you know those things are the bits that make a difference, but scaling that is a problem. Gotta be on it. Gotta be doing it and I don't think that the systems are in place at the moment. We have some digital channels that work OK, but not everybody engages like that. Like you said, voice is the one.

0:20:38.720 --> 0:20:39.220
 Steve Tomkinson
 Yeah.

0:20:28.920 --> 0:20:40.720
 tom
 Well, I didn't know exactly. Did, did you? No, no. Digital channels is nice. But I mean, if you you would use voice, it's much more interactive. It's much more human. It's much more personal, of course.

0:20:47.980 --> 0:20:48.280
 tom
 Yeah.

0:20:51.250 --> 0:20:52.640
 tom
 Actually, yeah.

0:20:41.160 --> 0:21:8.760
 Steve Tomkinson
 Knock, knock. I I think it's at what you're doing is you're instantly scaling up and you're you're turning that negative to a positive. And I think that's the the, the, the real core of it. Alright. Well look, I hope that was interesting for everybody. And thanks again for listening. And next week I think we're gonna be doing or next time around we are going to be doing a a demo of the voice box so we can hear him in action live.

0:21:9.590 --> 0:21:10.810
 Steve Tomkinson
 On the stage.

0:21:12.50 --> 0:21:12.730
 Steve Tomkinson
 Talking.

0:21:10.420 --> 0:21:14.470
 tom
 Yeah. Yeah. We're going to show the real world the real thing.

0:21:15.380 --> 0:21:15.570
 tom
 Ohh.

0:21:15.670 --> 0:21:15.970
 tom
 Ohh.

0:21:16.40 --> 0:21:16.420
 tom
 Ohh.

0:21:16.840 --> 0:21:19.360
 Steve Tomkinson
 We'll stop talking about it and let it talk for itself.

0:21:21.680 --> 0:21:22.410
 Steve Tomkinson
 Chantelle.

0:21:30.920 --> 0:21:31.590
 Steve Tomkinson
 Yeah, yeah.

0:21:18.540 --> 0:21:37.30
 tom
 Yeah, exactly. Stop talking about his show and show the world or show their listeners. Yeah, that, that it's really true. I mean, we're living 2023, and speech recognition is really working. It's really reliable. Not in 20 years ago, it wasn't. But today it is. And we just need to.

0:21:37.740 --> 0:21:40.880
 tom
 Make sure that everybody starts understanding.

0:21:41.100 --> 0:21:46.0
 Steve Tomkinson
 Yeah. So we'll have our. So we'll have a guest on which won't necessarily be a human.

0:21:45.630 --> 0:21:47.440
 tom
 No, no. We'll leave it as a surprise.

0:21:51.70 --> 0:21:53.200
 tom
 Mr Guest okay. Bye bye everybody.

0:21:49.170 --> 0:21:54.40
 Steve Tomkinson
 Alright. Thanks again, everybody. Cheerio. Cheers, Tom. Thanks. Now bye now. Bye.